{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:DJIX4I6FXOWQAV2NBQNNCKZS7K","short_pith_number":"pith:DJIX4I6F","schema_version":"1.0","canonical_sha256":"1a517e23c5bbad00574d0c1ad12b32fa8449b09896f75caf78e4207f8411fbac","source":{"kind":"arxiv","id":"1308.2694","version":1},"attestation_state":"computed","paper":{"title":"A Super-Fast Distributed Algorithm for Bipartite Metric Facility Location","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"James Hegeman, Sriram V. Pemmaraju","submitted_at":"2013-08-12T20:45:17Z","abstract_excerpt":"The \\textit{facility location} problem consists of a set of \\textit{facilities} $\\mathcal{F}$, a set of \\textit{clients} $\\mathcal{C}$, an \\textit{opening cost} $f_i$ associated with each facility $x_i$, and a \\textit{connection cost} $D(x_i,y_j)$ between each facility $x_i$ and client $y_j$. The goal is to find a subset of facilities to \\textit{open}, and to connect each client to an open facility, so as to minimize the total facility opening costs plus connection costs. This paper presents the first expected-sub-logarithmic-round distributed O(1)-approximation algorithm in the $\\mathcal{CONG"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1308.2694","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2013-08-12T20:45:17Z","cross_cats_sorted":[],"title_canon_sha256":"c893fec0329abf497f74288091e31abea6b6201a9eb105b1d7f4756cd5eacfdb","abstract_canon_sha256":"77445af9bc6dd82d7212829cf59d48d8d515769de53a9b86ae1540fedbbfb9f8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:16:05.443764Z","signature_b64":"Y6/VbsFhYbHW9hNsM5x+ttHUJSRGNd04EspLMUgiotePUtL2i1rsUEC/ziEGOSwm//W2I8LLU9fz9C0itlIZAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1a517e23c5bbad00574d0c1ad12b32fa8449b09896f75caf78e4207f8411fbac","last_reissued_at":"2026-05-18T03:16:05.443226Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:16:05.443226Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Super-Fast Distributed Algorithm for Bipartite Metric Facility Location","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"James Hegeman, Sriram V. Pemmaraju","submitted_at":"2013-08-12T20:45:17Z","abstract_excerpt":"The \\textit{facility location} problem consists of a set of \\textit{facilities} $\\mathcal{F}$, a set of \\textit{clients} $\\mathcal{C}$, an \\textit{opening cost} $f_i$ associated with each facility $x_i$, and a \\textit{connection cost} $D(x_i,y_j)$ between each facility $x_i$ and client $y_j$. The goal is to find a subset of facilities to \\textit{open}, and to connect each client to an open facility, so as to minimize the total facility opening costs plus connection costs. This paper presents the first expected-sub-logarithmic-round distributed O(1)-approximation algorithm in the $\\mathcal{CONG"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1308.2694","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1308.2694","created_at":"2026-05-18T03:16:05.443307+00:00"},{"alias_kind":"arxiv_version","alias_value":"1308.2694v1","created_at":"2026-05-18T03:16:05.443307+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1308.2694","created_at":"2026-05-18T03:16:05.443307+00:00"},{"alias_kind":"pith_short_12","alias_value":"DJIX4I6FXOWQ","created_at":"2026-05-18T12:27:43.054852+00:00"},{"alias_kind":"pith_short_16","alias_value":"DJIX4I6FXOWQAV2N","created_at":"2026-05-18T12:27:43.054852+00:00"},{"alias_kind":"pith_short_8","alias_value":"DJIX4I6F","created_at":"2026-05-18T12:27:43.054852+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DJIX4I6FXOWQAV2NBQNNCKZS7K","json":"https://pith.science/pith/DJIX4I6FXOWQAV2NBQNNCKZS7K.json","graph_json":"https://pith.science/api/pith-number/DJIX4I6FXOWQAV2NBQNNCKZS7K/graph.json","events_json":"https://pith.science/api/pith-number/DJIX4I6FXOWQAV2NBQNNCKZS7K/events.json","paper":"https://pith.science/paper/DJIX4I6F"},"agent_actions":{"view_html":"https://pith.science/pith/DJIX4I6FXOWQAV2NBQNNCKZS7K","download_json":"https://pith.science/pith/DJIX4I6FXOWQAV2NBQNNCKZS7K.json","view_paper":"https://pith.science/paper/DJIX4I6F","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1308.2694&json=true","fetch_graph":"https://pith.science/api/pith-number/DJIX4I6FXOWQAV2NBQNNCKZS7K/graph.json","fetch_events":"https://pith.science/api/pith-number/DJIX4I6FXOWQAV2NBQNNCKZS7K/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DJIX4I6FXOWQAV2NBQNNCKZS7K/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DJIX4I6FXOWQAV2NBQNNCKZS7K/action/storage_attestation","attest_author":"https://pith.science/pith/DJIX4I6FXOWQAV2NBQNNCKZS7K/action/author_attestation","sign_citation":"https://pith.science/pith/DJIX4I6FXOWQAV2NBQNNCKZS7K/action/citation_signature","submit_replication":"https://pith.science/pith/DJIX4I6FXOWQAV2NBQNNCKZS7K/action/replication_record"}},"created_at":"2026-05-18T03:16:05.443307+00:00","updated_at":"2026-05-18T03:16:05.443307+00:00"}